code: def forward(self, x):
      b, c, h, w = x.shape
  
      pos_embed = self._resize_pos_embed(
          self.pos_embed, h // self.patch_size, w // self.patch_size
      )
      x = self.patch_embed.proj(x).flatten(2).transpose((0, 2, 1))
  
      cls_tokens = self.cls_token.expand((b, -1, -1))
      x = paddle.concat((cls_tokens, x), axis=1)
  
      x = x + pos_embed
      x = self.pos_drop(x)
  
      outputs = []
      for index, blk in enumerate(self.blocks):
          x = blk(x)
          if index in [5, 11, 17, 23]:
              outputs.append(x)
  
      layer_1 = self.act_postprocess1[0:2](outputs[0])
      layer_2 = self.act_postprocess2[0:2](outputs[1])
      layer_3 = self.act_postprocess3[0:2](outputs[2])
      layer_4 = self.act_postprocess4[0:2](outputs[3])
  
      shape = (-1, 1024, h // self.patch_size, w // self.patch_size)
      layer_1 = layer_1.reshape(shape)
      layer_2 = layer_2.reshape(shape)
      layer_3 = layer_3.reshape(shape)
      layer_4 = layer_4.reshape(shape)
  
      layer_1 = self.act_postprocess1[3 : len(self.act_postprocess1)](
          layer_1
      )
      layer_2 = self.act_postprocess2[3 : len(self.act_postprocess2)](
          layer_2
      )
      layer_3 = self.act_postprocess3[3 : len(self.act_postprocess3)](
          layer_3
      )
      layer_4 = self.act_postprocess4[3 : len(self.act_postprocess4)](
          layer_4
      )
  
      return layer_1, layer_2, layer_3, layer_4
  
imports: import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleclas.ppcls.arch.backbone.model_zoo.vision_transformer import VisionTransformer
label_desc: Use image node_id 3 for calling the ViT obj's underlying member method code with example usage: obj.forward(x) and returns: layer_1,  layer_2,  layer_3,  layer_4